Context7
Up-to-date docs for AI agents
제작자가 쓴 설명(영어 원문)
Local-first, state-centric memory for coding agents. MCP server + CLI.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
MONET_STORAGE_DIR필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"monet": {
"command": "npx",
"args": [
"-y",
"@team-monet/monet",
"start"
],
"env": {
"MONET_STORAGE_DIR": "your-value"
}
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add monet --env MONET_STORAGE_DIR=your-value -- npx -y @team-monet/monet start실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"monet": {
"command": "npx",
"args": [
"-y",
"@team-monet/monet",
"start"
],
"env": {
"MONET_STORAGE_DIR": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"monet": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@team-monet/monet",
"start"
],
"env": {
"MONET_STORAGE_DIR": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
MONET_STORAGE_DIR env이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검
레지스트리 이름이 GitHub 계정 team-monet 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(1.12.0)은 어제 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 있어야 해요.
같은 카테고리에는: Context7, Codebase Memory, Exa
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
Up-to-date docs for AI agents
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Memory should change what your agent does.
🌐 [team-monet.com](https://team-monet.com/) · listed on the [MCP Registry](https://registry.modelcontextprotocol.io/v0.1/servers?search=io.github.team-monet/monet)
Monet is local-first memory for coding agents, built for the outcome you meant. It keeps what you and your team actually want — principles, rules, corrections — and delivers it while the agent works: principles always on, rules read at the moment they bind, corrections recorded so they never need making twice. It runs 100% locally (SQLite + on-device embeddings) and speaks MCP.
The easiest way to use Monet is to let your agent install and wire it for you. Paste one line into Claude Code (more agents coming soon):
Set up Monet for all my projects: read https://raw.githubusercontent.com/team-monet/monet/main/harness/bootstrap/install.md and follow it, checking with me at each step.
Your agent installs Monet, wires up the MCP server, and pulls in a memory-aware agent team — no manual config, no environment variables. That's the with-monet harness, which lives in harness/ in the Monet repo, and it's the recommended path.
⭐ If Monet helps, [star Monet on GitHub](https://github.com/team-monet/monet) — it's the best way to support the project.
Monet keeps one local store at ~/.monet and automatically organizes each project into its own *circle* — nothing to set up. Everything stays on your machine.
Run as many agent sessions as you like: they share one copy of the embedding model, so another session costs tens of megabytes rather than gigabytes. The first session that needs the model starts one background process (model-host) to hold it. It is reachable only by your own user, never over the network, and it exits by itself after a few idle minutes; the next session that needs it starts it again. It works through one request at a time, so a very long write makes other sessions wait. If it ever stops answering, the waiting call fails after ten minutes and says which process to end.
monet dashboardRun one command to open a local web view of your Monet memory as an explorable, force-directed graph:
monet dashboard
It opens in your browser automatically — if it doesn't (some Windows/headless setups), the terminal prints the URL (http://localhost:7373) and the store path; just visit that URL. The Graph tab is the main view: nodes are concepts (colored by kind, sized by importance), edges are the relationships between them, and a detail panel lets you read any concept's full body and evidence. The Concepts, Entities, Timeline, and Health tabs are sortable tables — Health surfaces contradictions, duplicates, and low-confidence concepts. If the graph looks empty, check the Store: line in the terminal: an empty graph usually means it's pointed at the wrong store (use -d) or the store is just new.
100% local. Fully offline. Strictly read-only. The server copies your store into a temporary snapshot on each request — the live database is never written to or locked. No network connections are made; run it with wifi off and the graph still renders.
monet dashboard # opens at http://localhost:7373
monet dashboard -p 8080 # -p, --port custom port monet dashboard -d ./path # -d, --dir point at a specific store
monet doctor / monet repairIf Monet reports an embedder pin mismatch, an interrupted embedding migration, malformed vectors, or an unavailable local model, start with the read-only diagnostic command:
monet doctor
monet doctor --check-provider # also load and probe the exact pinned provider monet doctor --dir ~/.monet --json # machine-readable result; diagnostics stay on stderr
doctor prints the absolute database path, SQLite integrity and schema, the durable model pin, all four live embedding populations (including dimensions and malformed-row samples), any migration sentinel, and copy-paste next commands. It does not construct MonetCore or alter the database. A healthy diagnosis exits 0; a completed diagnosis that needs recovery or provider action exits 2; inspection failures exit 1. An unavailable provider is reported separately from store safety—for example, an unsupported hashing tokenizer or missing ONNX cache does not by itself mean the database is corrupt. For an ONNX or custom model ID whose shape cannot be proven from the pin alone, --check-provider can reconcile an otherwise unknown assessment only when the exact provider loads and every clean live population has the same matching vector width.
A host that cannot start the server reports only that the connection closed — the transport does not exist until every fallible startup step has already succeeded, so there is no protocol channel left to explain a failure. The cause is written beside the store instead, at monet.db.startup-failure.json: the step it died in, the error and its code, the time, and the pid. The record is a sidecar of one database, named after it, so a directory holding more than one store never mixes their diagnoses. doctor prints that record on stderr before anything else, including when the store itself is too damaged to inspect.
The record holds only the most recent failure, and a later successful start does not clear it — hosts retry, so fail → fail → succeed is ordinary, and clearing on success would erase the evidence of the attempts that failed. Read the timestamp before acting on it.
Repairs are previews unless both confirmation flags are present. Choose exactly one mode:
# Preview a complete rewrite to a built-in provider alias.
monet repair --target hashing monet repair --target onnx
monet repair --target 'hashing:dim=256:tok=2' --json
monet repair --target hashing --apply --yes
monet repair --resume monet repair --resume --apply --yes
monet repair --abandon monet repair --abandon --apply --yes
Preview classifies the durable state before offering an apply command. An empty unpinned store or a clean, provider-compatible same-target store reports action: none; no backup or rewrite is needed, and --apply --yes refuses. Abandon preview also refuses unless a sentinel exists and core diagnostics classify it as safe. A valid target or resume preview loads and probes the exact provider but does not open the database for mutation. Apply preflights the provider again, takes exclusive SQLite ownership, and creates a verified backup before core can migrate schema or embeddings. Backups are automatic and cannot be disabled or redirected:
<storage-directory>/backups/monet-before-repair-<UTC>-<uuid>.db
The backup path is printed immediately and retained if later work fails. Stop other Monet processes if exclusive ownership cannot be acquired, then rerun the same command. Do not delete an active migration sentinel or edit the pin manually: use --resume, or use --abandon only when its preview says core classifies abandonment as safe. Successful previews and applies exit 0; invalid flags, provider failures, locks, unsafe abandon attempts, backup failures, and migration failures exit 1.
Monet is licensed under the GNU Affero General Public License v3.0 (AGPL-3.0-only). Full terms are in the LICENSE file included in this package. The with-monet harness is licensed separately under the Apache License 2.0.